3 steps to transform an ML prototype into a real-world ML app

Training Machine Learning models inside notebooks is just one step to building real-world ML services. And as exciting as it is, it brings no business value unless you deploy and operationalize the model, as a real-world ML app. In this article, you will learn how to transform an all-in-one Jupyter notebook with data preparation and …

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Real-time feature engineering with Python

Real-time ML is a fascinating topic, which I wanna go deeper into in the following weeks and months. Because of this, I started creating a sequence of small projects where I build real-time products, beginning with a real-time feature engineering pipeline. Real-time feature engineering A real-time feature pipeline is a program that ingests real-time raw data (e.g. …

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